Extrinsic Calibration of an Eye-In-Hand 2D LiDAR Sensor in Unstructured Environments Using ICP

Arne Peters,Alois C Knoll,Adam Schmidt

doi:10.1109/lra.2020.2965878

Abstract

We propose a calibration method for the six degrees of freedom (DOF) extrinsic pose of a 2D laser rangefinder mounted to a robot arm. Our goal is to design a system that allows on-site re-calibration without requiring any kind of special environment or calibration objects. By moving the sensor we generate 3D scans of the surrounding area on which we run a iterative closest point (ICP) variant to estimate the missing part of the kinematic chain. With this setup we can simply scale the density and format of our 3D scan by adjusting the robot speed and trajectory, allowing us to exploit the power of a high resolution 3D scanner for a variety of tasks such as mapping, object recognition and grasp planning. Our evaluation, performed on synthetic datasets as well as from real-data shows that the presented approach provides good results both in terms of convergence on crude initial parameters as well as in the precision of the final estimate.

Highlights

E YE-IN-HAND sensors offer a great potential to mobile robotics as they allow capturing of data that is not visible to their static counterparts
2) We show an iterative closest point (ICP) variant to calibration the mounting pose of a 2D lidar sensor on a robot arm – which is to our best knowledge the first solution to this problem capable of estimating the full 6 degrees of freedom (DOF) pose of such an eye-in-hand sensor without using an external calibration object
We presented an easy to use method for calibrating the extrinsic pose of a 2D rangefinder mounted to a robot arm

Summary

Introduction

E YE-IN-HAND sensors offer a great potential to mobile robotics as they allow capturing of data that is not visible to their static counterparts. To make use of such scan data the relative pose of the sensor to the robots end-effector needs to be exactly known. If a system becomes uncalibrated after a repair, a collision with its environment or other mechanical stress as i.e. from transportation, the results of its processing of sensor data can become worse or even useless. The consequences of such a situation can reach from simple loss cost of time or money over an abortion of mission in case the re-calibration cannot be Manuscript received September 10, 2019; accepted December 31, 2019. This letter was recommended for publication by Associate Editor H.

Objectives

Results

Conclusion